In blind equalization, the adaptive filters of a receiver are converged without the use of a training signal. As known in the art, there are two techniques for blind equalization: one is referred to herein as the "reduced constellation algorithm" (RCA) (e.g., see Y. Sato, "A Method of Self-Recovering Equalization for Multilevel Amplitude-Modulation Systems," IEEE Trans. Commun., pp. 679-682, Jun. 1975; and U.S. Pat. No. 4,227,152, issued Oct. 7, 1980 to Godard); and the other technique is the so-called "constant modulus algorithm" (CMA) (e.g., see D. N. Godard, "Self-Recovering Equalization and Carrier Tracking in Two-Dimensional Data Communications Systems," IEEE Trans. Commun., vol. 28, no. 11, pp. 1867-1875, November 1980; and N. K. Jablon, "Joint Blind Equalization, Carrier Recovery, and Timing Recovery for High-Order QAM Signal Constellations", IEEE Trans. Signal Processing, vol. 40, no. 6, pp. 1383-1398, 1992.) Further, the co-pending, commonly assigned, U.S. Patent application of Werner et al., entitled "Blind Equalization," Ser. No. 08/646404, filed on May 7, 1996, presents an new blind equalization technique--the multimodulus algorithm (MMA)--as an alternative to the above-mentioned RCA and CMA approaches.
However, for all blind equalization approaches the most fundamental performance issue is the ability to achieve reliable initial convergence--else the adaptive filter may converge to a wrong solution such as the well-known "diagonal solution."
Generally speaking, the RCA algorithm has less reliable convergence than either the CMA or MMA algorithms. As between the CMA and MMA algorithms, these algorithms have both benefits and drawbacks. For example, the CMA algorithm provides more reliable convergence--thus avoiding incorrect diagonal solutions--but the CMA algorithm requires an expensive rotator. In comparison, the MMA algorithm does not require an expensive rotator but is more susceptible than the CMA algorithm to incorrect convergence.
The U.S. Patent applications of: Werner et al., present alternative techniques for use in preventing diagonal solutions. The Werner et al. U.S. Patent application entitled "Technique for Improving the Blind Convergence of a Two-Filter Adaptive Equalizer," Ser. No. 08/717,582, filed on Sep. 18, 1996, presents a blind equalization algorithm referred to as the constrained Hilbert cost function (CHCF). The CHCF algorithm uses the Hilbert transfer function and dot-product properties of the in-phase and quadrature filters to prevent the occurrence of diagonal solutions. The Werner et al. U.S. Patent application entitled "Technique for Improving the Blind Convergence of an Adaptive Equalizer Using a Transition Algorithm," Ser. No. 08/744,908, filed on Nov. 8, 1996, presents a blind equalization technique algorithm referred to as the transition algorithm. In the latter, generally speaking, an adaptive filter first uses the CMA algorithm and then switches to using the MMA algorithm.